View source: R/VariantQuantileThresholding_Combined.R
VariantQuantileThresholding_Combined | R Documentation |
We get variants of interest using the quantile thresholding. This function combines the functions VariantSelection_Quantile, VariantSelection_Group and VariantSelection_TopCells. If you use top_cells and top_VAF, you have to only supply one quantil value (quantiles = 0.9, thresholds = 0). This function is adapted from the Peter van Galen. Source: https://github.com/petervangalen/MAESTER-2021
VariantQuantileThresholding_Combined(
SE,
min_coverage = 2,
quantiles = c(0.1, 0.9),
thresholds = c(0.1, 0.9),
top_cells = NULL,
top_VAF = NULL,
min_quality = NULL,
mean_allele_frequency = 0,
group_of_interest = NULL,
group1 = NULL,
group2 = NULL,
group_factor = NULL,
remove_nocall = TRUE,
verbose = TRUE
)
SE |
SummarizedExperiment object. |
min_coverage |
Minimum coverage needed. |
quantiles |
The lower and upper quantile you want to use. |
thresholds |
The VAF thresholds you want to use for the quantiles. |
top_cells |
The number of cells with at least top_VAF percent for a variant. |
top_VAF |
The VAF for the top cells. |
min_quality |
The minimum quality you want for the Variants of Interest. Can be ignored by setting it to NULL. |
mean_allele_frequency |
The minimum mean allele frequency. Default = 0 |
group_of_interest |
The column data that divides the cells. |
group1 |
The first group of interest. If set, the quantiles are only calculated for this group. |
group2 |
The second group of interest. |
group_factor |
How much higher has the mean allele frequency to be in group 1 when compared to group 2? |
remove_nocall |
Should NoCall cells (consensus = 0) be disregarded during the analysis? |
verbose |
Should the function be verbose? Default = TRUE |
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